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40 Jahre Hochschulrahmengesetz
Get PDFNach einer fast sechsjährigen Entstehungsgeschichte wurde das Hochschulrahmengesetz (HRG) im Dezember 1975 bundesweit verabschiedet und trat am 30. Januar 1976 in Kraft. Sowohl im Vorfeld – schon 1971 hatten deutschlandweit Studierende gegen die geplante Einführung eines Hochschulrahmengesetzes auf Bundesebene protestiert – als auch nach Inkrafttreten des Gesetzes wurde es von Hochschulleitern, Wissenschaftlern und Studierenden massiv kritisiert
55 Jahre im Dienste der TH Darmstadt: Heinrich Hohenner, Professor für Geodäsie
Get PDFHeinrich Hohenner wurde am 07.12.1874 in Wunsiedel (Oberfranken) geboren. Zunächst besuchte er von 1890 bis 1892 die Industrieschule in Nürnberg. Im Anschluss begann er ein Studium im Fach Geodäsie an der TH München, welches er 1894 mit dem Diplom abschloss. Anschließend arbeitete er 1894 für das Messungsamt in Wunsiedel. 1896 kehrte er als wissenschaftlicher Assistent an die TH München zurück und legte die Staatsprüfung für Vermessungsingenieure ab. Zwischen 1898 und 1902 lehrte er an der TH München als Privatdozent, ehe er 1902 dem Ruf der TH Stuttgart auf ein Extraordinariat für Geodäsie folgte. Gleichzeitig promovierte er 1904 zum Dr.-Ing. an der TH München. Im Jahr 1907 berief ihn die TH Braunschweig zum ordentlichen Professor für Geodäsie. Dort verfasste er sein bekanntes Lehrbuch »Geodäsie« (1910)
Advancing Reynolds-Averaged Navier–Stokes Turbulence Models with Machine Learning and Data-Driven Methods
Get PDFReynolds-averaged Navier-Stokes (RANS) methods are fundamental to turbulent flow simulations in industrial and technical applications, offering computational efficiency by solving the equations for statistically averaged flow fields while incorporating the effects of unresolved turbulence through modeling the Reynolds stress tensor. This thesis investigates the application of machine learning and data-driven methods to advance RANS turbulence modeling, intending to derive accurate, robust and generalizable models and model augmentations. Two complementary studies address eddy viscosity models and Reynolds stress models individually.
The first study applies the Field Inversion and Machine Learning (FIML) framework to augment the k-omega SST model, enhancing its ability to predict flow separation and reattachment in wall-bounded flows over smooth, curved surfaces. A correction term is introduced into the omega-equation to mitigate the underprediction of turbulence intensity in separated shear layers. Field inversion is used to determine the spatial distribution of the correction term for various flow configurations, and a neural network is trained on this data to represent the correction term based on local invariant flow features. RANS computations incorporating the neural network-augmented k-omega SST model achieved accurate predictions of separating flows while avoiding unnecessary corrections in undisturbed flow regions. An algebraic, closed-form correction term has been derived subsequently, showing accurate predictive performance, even for cases significantly different from those used in the development.
The second study introduces a novel approach for modeling the pressure redistribution term for second-moment closure modeling in Reynolds stress models. This approach integrates a neural network into a conventional algebraic formulation, enabling the neural network outputs to represent the formulation's coefficients as a functional relationship based on local invariant flow features.
The neural network demonstrated good predictive accuracy based on the data, with coefficients in free-stream conditions closely aligning with those from physically grounded models. However, applying the neural network in a near-wall baseline RSM did not achieve convergent solutions in RANS computations. An algebraic formulation resembling the neural network model has been developed, incorporating insights gained from RANS computation to ensure accuracy and robustness in channel and boundary layer flow cases when implemented within the baseline RSM
Entropy based blending of policies for multi-agent coexistence
Get PDFResearch on multi-agent interaction involving humans is still in its infancy. Most approaches have focused on environments with collaborative human behavior or a small, defined set of situations. When deploying robots in human-inhabited environments in the future, the diversity of interactions surpasses the capabilities of pre-trained collaboration models. ”Coexistence” environments, characterized by agents with varying or partially aligned objectives, present a unique challenge for robotic collaboration. Traditional reinforcement learning methods fall short in these settings. These approaches lack the flexibility to adapt to changing agent counts or task requirements without undergoing retraining. Moreover, existing models do not adequately support scenarios where robots should exhibit helpful behavior toward others without compromising their primary goals. To tackle this issue, we introduce a novel framework that decomposes interaction and task-solving into separate learning problems and blends the resulting policies at inference time using a goal inference model for task estimation. We create impact-aware agents and linearly scale the cost of training agents with the number of agents and available tasks. To this end, a weighting function blending action distributions for individual interactions with the original task action distribution is proposed. To support our claims we demonstrate that our framework scales in task and agent count across several environments and considers collaboration opportunities when present. The new learning paradigm opens the path to more complex multi-robot, multi-human interactions
Self‐optimizing Cobalt Tungsten Oxide Electrocatalysts toward Enhanced Oxygen Evolution in Alkaline Media
Get PDFSelf‐optimizing mixed metal oxides represent a novel class of electrocatalysts for the advanced oxygen evolution reaction (OER). Here, we report self‐assembled cobalt tungsten oxide nanostructures on a lab‐synthesized copper oxide substrate through a single‐step deposition approach. The resulting composite exhibits remarkable self‐optimization behavior, shown by significantly reduced overpotentials and enhanced current densities, accompanied with substantial increase in OER kinetics, electrocatalytically active surface area, surface wettability, and electrical conductivity. Under operating conditions, interfacial restructuring of the electrocatalyst reveals the in situ formation of oxidized cobalt species as the true active site. Complementary density functional theory (DFT) calculations further demonstrate the formation of *OOH intermediate as the rate‐determining step of OER, and highlight the adaptive binding of oxygen intermediates, which transitions from tungsten to cobalt site during OER process. Our study provides a fundamental understanding of the self‐optimization mechanism and advances the knowledge‐driven design of efficient water‐splitting electrocatalysts
Synthesis and Application of a Hydrophobic Polyglutamate Bearing a Triphenylphosphine Group for the Orientation of Pharmaceutically Active Compounds and the Measurement of Residual Dipolar Couplings
Get PDFFor structure elucidation purposes, it is highly desirable to partially retain anisotropic observables in high-resolution NMR spectra, as they provide valuable information about the relative configuration, conformation, and dynamics of compounds in solution. Alignment media based on lyotropic liquid crystalline phases formed by α-helical polypeptides can be used to achieve weak solute alignment. We present a novel homopolyglutamate bearing a bulky and hydrophobic triphenylphosphine side chain, which proved to be an excellent alignment medium using chloroform as a co-solvent. We successfully applied the alignment medium for the measurement of residual dipolar couplings (RDCs) of artemisinin, an antimalarial drug, galantamine, which is used to treat Alzheimer's disease, and vincamine, a cerebral vasodilator and potential anti-cancer agent. Excellent agreement between experimental and back-calculated RDCs is obtained, and the enantio-differentiating property of the new medium is demonstrated using the model compound isopinocampheol. Our results show that this alignment medium is of high interest for elucidating compounds characterized by high complexity and relevance in the research field of small molecule pharmaceuticals
Assure or Insure Cyber Risk? Nonprofessional Investors' Willingness to Invest
Get PDFOrganizations face severe cyber risks, which may lead companies to contract related insurance or to demand cybersecurity assurance services to signal risk management. This paper experimentally investigates how cybersecurity assurance and insurance against cyber risks impact nonprofessional investors. We conducted an experiment with a 2 × 2 between‐subjects design with 100 UK nonprofessional investors and manipulated the assurance provision and insurance purchase to analyze their impact on willingness to invest. Our results suggest that cybersecurity assurance and cyber risk insurance positively affect willingness to invest. The results confirm the usefulness of measures to handle cyber risks and are of interest to managers, auditors, regulators, and academics
‚Deutsch‘ als kunsthistorische Kategorie : Zur sprachlichen Prägung nationaler Identität in deutschen Kunstgeschichten
No full text„Wer bin ich?“ Antworten auf diese unscheinbare Frage werden gemeinhin unter dem Schlagwort ‚Identität‘ zusammengefasst.2 Mit ‚Identität‘ wird also eine offene Klasse von Aussagen benannt, die alle eines gemeinsam haben: Sie erwachsen aus einem Akt der Selbstbeschreibung des Einzelnen. In der Regel greift man dazu auf gesellschaftliche Rollenmodelle zurück, die dann individuell ausgestaltet werden, indem man Übereinstimmungen und Abweichungen vom jeweiligen Prototypen verzeichnet. Eines dieser Modelle ist das des Zugehörigen zu einer Nation: „Wer bin ich? Ich bin Deutscher!“ Die Geschichte dieses Selbstzuschreibungsmusters ist bekannt: Es gewinnt im Zuge der nationalen Emanzipationsbewegung des 19. Jhs. zunehmend an Bedeutung, wird im 20. Jh. mit den bekannten Folgen nationalsozialistisch aufgeladen und verschwindet nach 1945 im Untergrund. Erst in der jüngsten Vergangenheit werden nationale Zuschreibungsfiguren im Zuge einer an der Globalisierung orientierten Perspektive – gleichsam als Regionalismus zweiter Ordnung – wieder gesellschaftsfähig
(In)consistency in European external energy governance in the EU's southern neighbourhood - The case of Morocco
Get PDFEnergy is a strategic product cutting across a variety of domains including (geo)politics and economics, as well as climate and the environment. The achievement of a secure, affordable and sustainable energy supply is at the heart of any economy. In this context, changes in global energy markets have a decisive impact on energy politics, calling for a coherent and consistent governance approach in order to remain competitive. Yet, as for the EU, the achievement of consistency is one of its greatest challenges, notably when it comes to external policies. This is also an issue with respect to energy. In fact, recent developments in the global energy landscape and international events such as climate change increasingly involve the Union in relations of interdependence with its neighbouring countries, including those located to its south. However, whilst energy has always been a key area of cooperation in EU-southern Mediterranean relations and although the Union has long recognised the region’s potential in this regard, past efforts at building a fruitful energy relationship have been rather disappointing. This is problematic in so far as a shift in traditional energy policy cooperation in the region has been observed in recent years, mirroring deep geopolitical change. Adding to this, the perceptibility of EU energy policies in the region is overall low. Against this background, this dissertation examined policy (in)consistency in EU energy governance towards the southern Mediterranean, using Morocco as a case study. In fact, Morocco is not only the EU’s most important partner country within the European Neighbourhood Policy (ENP) framework but is also of utmost importance for the EU’s energy and climate interests, notably when it comes to a clean energy turnaround. Moreover, the country has long been neglected as a research subject in the literature and is therefore or academic interest.
The aim of this research was to explore whether and to what extent the EU is consistent in its energy governance approach towards Morocco and to determine the reasons for consistency or inconsistency, the context in which a total of three factors have been identified, namely competencies, interests and interdependencies. To assess consistency, this research used coordination as a proxy variable for consistency, whereby, inspired by the Les Metcalfe methodology, it attempted to investigate the coordination mechanisms of the different actors involved in EU energy governance towards Morocco, including the horizontal, vertical and diagonal dimensions as well as in the EU multilevel system and at the third-country level. As one outcome of this analysis, it has transpired that coordination (and thus consistency) takes place with regard to different aspects (strategic/political or functional, i.e. when it centres around financial or technical issues). Whilst strategic/political coordination takes place mainly in the EU multilevel system, functional coordination takes place in both the EU multilevel system and at the third-country level. Another outcome is that strategic/political coordination is overall more extensive in the horizontal and diagonal dimensions, but less extensive in the intergovernmental and vertical dimensions, whereas functional coordination seems to run smoothly in all dimensions. One reason for the extensive horizontal and diagonal coordination seem to be the clear delimitation of competencies. The extensive functional coordination in the intergovernmental and vertical dimensions is due to converging energy interests across the EU institutions and member states. By contrast, the less extensive strategic/political coordination in these two dimensions can be explained by diverging policy interests as regards EU energy governance towards Morocco and interdependencies between the member states and Morocco
Highly active iron catalysts for olefin hydrogenation enable para-hydrogen induced hyperpolarisation of ¹H and ¹⁹F NMR resonances at 1.4 Tesla
Get PDFpara-Hydrogen induced polarisation (PHIP) is an excellent tool for extracting mechanistic information in catalysis since it circumvents the intrinsic low sensitivity of nuclear magnetic resonance (NMR) spectroscopy. We report a class of iron complexes that are highly active in olefin hydrogenation catalysis and act as PHIP catalysts at 1.4 Tesla. Moreover, hyperpolarisation transfer to ¹⁹F is observed